Systems and Methods for Message Pushing

1. A method for pushing messages, the method comprising: upon receiving a push trigger message, acquiring one or more first user identifiers corresponding to the push trigger message; in response to the acquired first user identifiers being in a predetermined target user group, selecting one or more first push messages based on at least information associated with a first promotion type of the target user group; and pushing the first push messages based on at least information associated with the first user identifiers, wherein the target user group includes a plurality of second user identifiers and is generated by statistical processing of first user attributes of registered user identifiers based on at least information associated with a predetermined first forecast model, wherein the method further comprises: selecting, randomly, one or more fourth user identifiers from login user identifiers to obtain a second user group, the fourth user identifiers corresponding to information associated with a third promotion type and one or more fourth user attributes; pushing one or more second push messages corresponding to the third promotion type of the second user group upon detecting a third push trigger message initiated by the fourth user identifiers in the second user group; receiving one or more second response messages returned by the fourth user identifiers in the second user group; recording a third number of the second push messages and a fourth number of the second response messages during a second predetermined time period; determining a second ratio of the third number of the second push messages and the fourth number of the second response messages as a success rate threshold; and configuring the first forecast model based on a comparison result between a push success rate of a predetermined initial forecast model and the success rate threshold.

2. The method of claim 1 , wherein the configuring the first forecast model includes: selecting one or more forecast user identifiers from the registered user identifiers; classifying the forecast user identifiers based on at least information associated with second user attributes of the forecast user identifiers; obtaining a first user group associated with a second promotion type; calculating third user attributes of one or more third user identifiers in the obtained first user group based on at least information associated with the initial forecast model to generate a forecast user group; sending the first push messages based on at least information associated with the forecast user group; determining a push success rate of the initial forecast model based on at least information associated with a first number of the first push messages and a second number of first response messages; and in response to the push success rate exceeds the success rate threshold, configuring the initial forecast model as the first forecast model.

3. The method of claim 2 , wherein the calculating third user attributes of one or more third user identifiers in the obtained first user group based on at least information associated with a predetermined initial forecast model to generate a forecast user group includes: acquiring first user data related to the third user attributes of the third user identifiers in the first user group; performing information-entropy calculation on the first user data to obtain information entropy related to the third user attributes; determining one or more target user attributes based on at least information associated with the information entropy; extracting one or more target user identifiers related to the target user attributes, second user data related to the target user identifiers exceeding a predetermined data threshold; and generating the forecast user group corresponding to a second promotion type based on at least information associated with the target user identifiers.

4. The method of claim 2 , wherein the sending the first messages based on at least information associated with the forecast user group and the determining a push success rate of the initial forecast model based on at least information associated with a first number of the first push messages and a second number of first response messages include: pushing the first push messages corresponding to the first promotion type of the target user group upon detecting a second push trigger message initiated by the forecast user identifiers in the forecast user group; receiving the first response messages returned by the forecast user identifiers in the forecast user group; recording the first number of the first push messages and the second number of the first response messages during a first predetermined time period; and determining a first ratio between the first number and the second number as the push success rate.

5. The method of claim 1 , further comprising: in response to the push success rate not exceeding the success rate threshold, modifying the second user attributes of the forecast user identifiers in the forecast user group corresponding to the second promotion type to configure to the first forecast model.

6. The method of claim 5 , further comprising: detecting whether an update cycle arrives; and in response to the update cycle arriving, configuring the forecast model.

7. A message-push device comprising: an acquisition module configured to, upon receiving a push trigger message, acquire one or more first user identifiers corresponding to the push trigger message; and a push module configured to, in response to the acquired first user identifiers being in a predetermined target user group, select one or more first push messages based on at least information associated with a first promotion type of the target user group and push the first push messages based on at least information associated with the first user identifiers; wherein the target user group includes a plurality of second user identifiers and is generated by statistical processing of first user attributes of registered user identifiers based on at least information associated with a predetermined first forecast model, wherein the message-push device further comprises: a selection module configured to select, randomly, one or more fourth user identifiers from login user identifiers to obtain a second user group, the fourth user identifiers corresponding to information associated with a third promotion type and one or more fourth user attributes; wherein the push module is further configured to push one or more second push messages corresponding to the third promotion type of the second user group upon detecting a third push trigger message initiated by the fourth user identifiers in the second user group; a reception module configured to receive one or more second response messages returned by the fourth user identifiers in the second user group; a threshold determination module configured to record a third number of the second push messages and a fourth number of the second response messages during a second predetermined time period and determine a second ratio of the third number of the second push messages and the fourth number of the second response messages as a success rate threshold; and a configuration module configured to configure the first forecast model based on a comparison result between a push success rate of a predetermined initial forecast model and the success rate threshold.

8. The device of claim 7 , wherein the configuration module includes: a selection unit configured to select one or more forecast user identifiers from the registered user identifiers, classify the forecast user identifiers based on at least information associated with second user attributes of the forecast user identifiers, and obtain a first user group associated with a second promotion type; a generation unit configured to calculate third user attributes of one or more third user identifiers in the obtained first user group based on at least information associated with the initial forecast model to generate a forecast user group; a determination unit configured to send the first push messages based on at least information associated with the forecast user group and determine a push success rate of the initial forecast model based on at least information associated with a first number of the first push messages and a second number of first response messages; and a configuration unit configured to, in response to the push success rate exceeds the success rate threshold, configure the initial forecast model as the first forecast model.

9. The device of claim 8 , wherein the generation unit includes: an acquisition subunit configured to acquire first user data related to the third user attributes of the third user identifiers in the first user group and perform information-entropy calculation on the first user data to obtain information entropy related to the third user attributes; a determination subunit configured to determine one or more target user attributes based on at least information associated with the information entropy; and a generation subunit configured to extract one or more target user identifiers related to the target user attributes, second user data related to the target user identifiers exceeding a predetermined data threshold, and generate the forecast user group corresponding to a second promotion type based on at least information associated with the target user identifiers.

10. The device of claim 8 , wherein the determination unit includes: a push subunit configured to push the first push messages corresponding to the first promotion type of the target user group upon detecting a second push trigger message initiated by the forecast user identifiers in the forecast user group; a reception subunit configured to receive the first response messages returned by the forecast user identifiers in the forecast user group; and a determination subunit configured to record the first number of the first push messages and the second number of the first response messages during a first predetermined time period and determine a first ratio between the first number and the second number as the push success rate.

11. The device of claim 8 , further comprising: a modification module configured to, in response to the push success rate not exceeding the success rate threshold, modify the second user attributes of the forecast user identifiers in the forecast user group corresponding to the second promotion type to configure to the first forecast model.

12. The device of claim 11 , further comprising: a detection module configured to detect whether an update cycle arrives and, in response to the update cycle arriving, configure the forecast model.

13. The device of claim 7 , further comprising: one or more data processors; and a computer-readable storage medium; wherein the acquisition module and the push module are stored in the storage medium and configured to be executed by the one or more data processors.

14. A message-push server comprising: a message-push device; wherein the message-push device includes: an acquisition module configured to, upon receiving a push trigger message, acquire one or more first user identifiers corresponding to the push trigger message; and a push module configured to, in response to the acquired first user identifiers being in a predetermined target user group, select one or more first push messages based on at least information associated with a first promotion type of the target user group and push the first push messages based on at least information associated with the first user identifiers; wherein the target user group includes a plurality of second user identifiers and is generated by statistical processing of first user attributes of registered user identifiers based on at least information associated with a predetermined first forecast model, wherein the message-push device further includes: a selection module configured to select, randomly, one or more fourth user identifiers from login user identifiers to obtain a second user group, the fourth user identifiers corresponding to information associated with a third promotion type and one or more fourth user attributes; wherein the push module is further configured to push one or more second push messages corresponding to the third promotion type of the second user group upon detecting a third push trigger message initiated by the fourth user identifiers in the second user group; a reception module configured to receive one or more second response messages returned by the fourth user identifiers in the second user group; and a threshold determination module configured to record a third number of the second push messages and a fourth number of the second response messages during a second predetermined time period and determine a second ratio of the third number of the second push messages and the fourth number of the second response messages as a success rate threshold; and a configuration module configured to configure the first forecast model based on a comparison result between a push success rate of a predetermined initial forecast model and the success rate threshold.

15. The server of claim 14 , wherein the configuration module includes: a selection unit configured to select one or more forecast user identifiers from the registered user identifiers, classify the forecast user identifiers based on at least information associated with second user attributes of the forecast user identifiers, and obtain a first user group associated with a second promotion type; a generation unit configured to calculate third user attributes of one or more third user identifiers in the obtained first user group based on at least information associated with the initial forecast model to generate a forecast user group; a determination unit configured to send the first push messages based on at least information associated with the forecast user group and determine a push success rate of the initial forecast model based on at least information associated with a first number of the first push messages and a second number of first response messages; and a configuration unit configured to, in response to the push success rate exceeds the success rate threshold, configure the initial forecast model as the first forecast model.

16. The server of claim 15 , wherein the generation unit includes: an acquisition subunit configured to acquire first user data related to the third user attributes of the third user identifiers in the first user group and perform information-entropy calculation on the first user data to obtain information entropy related to the third user attributes; a determination subunit configured to determine one or more target user attributes based on at least information associated with the information entropy; and a generation subunit configured to extract one or more target user identifiers related to the target user attributes, second user data related to the target user identifiers exceeding a predetermined data threshold, and generate the forecast user group corresponding to a second promotion type based on at least information associated with the target user identifiers.

17. The server of claim 15 , wherein the determination unit includes: a push subunit configured to push the first push messages corresponding to the first promotion type of the target user group upon detecting a second push trigger message initiated by the forecast user identifiers in the forecast user group; a reception subunit configured to receive the first response messages returned by the forecast user identifiers in the forecast user group; and a determination subunit configured to record the first number of the first push messages and the second number of the first response messages during a first predetermined time period and determine a first ratio between the first number and the second number as the push success rate.

18. The server of claim 14 , wherein the message-push device further includes: a modification module configured to, in response to the push success rate not exceeding the success rate threshold, modify the second user attributes of the forecast user identifiers in the forecast user group corresponding to the second promotion type to configure to the first forecast model.

19. The server of claim 18 , wherein the message-push device further includes: a detection module configured to detect whether an update cycle arrives and, in response to the update cycle arriving, configure the forecast model.

20. A non-transitory computer readable storage medium comprising programming instructions for pushing messages, the programming instructions configured to cause one or more data processors to execute operations comprising: upon receiving a push trigger message, acquiring one or more first user identifiers corresponding to the push trigger message; in response to the acquired first user identifiers being in a predetermined target user group, selecting one or more first push messages based on at least information associated with a first promotion type of the target user group; and pushing the first push messages based on at least information associated with the first user identifiers, wherein the target user group includes a plurality of second user identifiers and is generated by statistical processing of first user attributes of registered user identifiers based on at least information associated with a predetermined first forecast model, wherein the programming instructions are further configured to cause the one or more data processors to execute; selecting, randomly, one or more fourth user identifiers from login user identifiers to obtain a second user group, the fourth user identifiers corresponding to information associated with a third promotion type and one or more fourth user attributes; pushing one or more second push messages corresponding to the third promotion type of the second user group upon detecting a third push trigger message initiated by the fourth user identifiers in the second user group; receiving one or more second response messages returned by the fourth user identifiers in the second user group; recording a third number of the second push messages and a fourth number of the second response messages during a second predetermined time period; determining a second ratio of the third number of the second push messages and the fourth number of the second response messages as a success rate threshold; and configuring the first forecast model based on a comparison result between a push success rate of a predetermined initial forecast model and the success rate threshold.